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COMBINING PHENOTYPIC AND RESTING-STATE FMRI DATA FOR AUTISM CLASSIFICATION WITH RECURRENT NEURAL NETWORKS

Accurate identification of autism spectrum disorder (ASD) from resting-state functional magnetic resonance imaging (rsfMRI) is a challenging task due in large part to the heterogeneity of ASD. Recent work has shown better classification accuracy using a recurrent neural network with rsfMRI time-seri...

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Detalhes bibliográficos
Publicado no:Proc IEEE Int Symp Biomed Imaging
Main Authors: Dvornek, Nicha C., Ventola, Pamela, Duncan, James S.
Formato: Artigo
Idioma:Inglês
Publicado em: 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6166875/
https://ncbi.nlm.nih.gov/pubmed/30288208
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI.2018.8363676
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